There Is No Preview Available For This Item
This item does not appear to have any files that can be experienced on Archive.org.
Please download files in this item to interact with them on your computer.
Show all files
With a large percentage of total system cost going to system administration tasks, self-management remains a difficult and important goal in systems. As a step towards the self-management vision, I will present a framework we have developed that enables systems to be self-predicting and answer “what-if” questions about their behavior with little or no administrator involvement. We have built a Resource Advisor inside two real systems: Microsoft's SQL Server database and the Ursa Minor storage system at Carnegie Mellon University. The Resource Advisor helps with upgrade and data placement decisions and provides what-if interfaces to external administrators (and internal tuning modules). The Resource Advisor is based on efficient system behavioral models that enable robust predictions in multi-tier systems.